Journal ArticleDOI
Speech enhancement using 2-D Fourier transform
Ing Yann Soon,Soo Ngee Koh +1 more
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TLDR
This paper presents an innovative way of using the two-dimensional (2-D) Fourier transform for speech enhancement and proposes a hybrid filter which effectively combines the one-dimensional Wiener filter with the 2-DWiener filter.Abstract:
This paper presents an innovative way of using the two-dimensional (2-D) Fourier transform for speech enhancement. The blocking and windowing of the speech data for the 2-D Fourier transform are explained in detail. Several techniques of filtering in the 2-D Fourier transform domain are also proposed. They include magnitude spectral subtraction, 2-D Wiener filtering as well as a hybrid filter which effectively combines the one-dimensional (1-D) Wiener filter with the 2-D Wiener filter. The proposed hybrid filter compares favorably against other techniques using an objective test.read more
Citations
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Journal ArticleDOI
/spl beta/-order MMSE spectral amplitude estimation for speech enhancement
TL;DR: E evaluation results show that the proposed /spl beta/-order minimum mean-square error speech enhancement approach can achieve a more significant noise reduction and a better spectral estimation of weak speech spectral components from a noisy signal as compared to many existing speech enhancement algorithms.
Journal ArticleDOI
A spectral filtering method based on hybrid wiener filters for speech enhancement
TL;DR: This paper proposes a single channel speech enhancement system which exploits such correlations between the different time frames to further reduce residual noise and results in pleasant sounding speech for human listeners.
Journal ArticleDOI
Noise reduction for periodic signals using high-resolution frequency analysis
TL;DR: This work examined the effect of the frequency resolution on noise reduction using NHA rather than DFT as the preprocessing step of the noise reduction process, and found NHA to be superior to DFT, providing an approximately 2 dB improvement in SNR.
Patent
Gain-constrained noise suppression
TL;DR: In this article, the spectrum values are grouped into frequency bins, and a noise characteristic is estimated for each bin classified as a noise bin, and an energy parameter is smoothed in both the time domain and the frequency domain to improve noise estimation per bin.
Journal ArticleDOI
Identification of ultrasound contrast agent dilution systems for ejection fraction measurements
TL;DR: The results are promising and show a 0.93 correlation coefficient with echographic bi-plane ejection fraction measurements, and a more extensive validation as well as an investigation on the method applicability for valve insufficiency and right ventricular ejections fraction quantification will be an object of future study.
References
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Journal ArticleDOI
Suppression of acoustic noise in speech using spectral subtraction
TL;DR: A stand-alone noise suppression algorithm that resynthesizes a speech waveform and can be used as a pre-processor to narrow-band voice communications systems, speech recognition systems, or speaker authentication systems.
Journal ArticleDOI
Speech enhancement using a minimum-mean square error short-time spectral amplitude estimator
Yariv Ephraim,David Malah +1 more
TL;DR: In this article, a system which utilizes a minimum mean square error (MMSE) estimator is proposed and then compared with other widely used systems which are based on Wiener filtering and the "spectral subtraction" algorithm.
Journal Article
Speech enhancement using a minimum mean square error short-time spectral amplitude estimator
TL;DR: This paper derives a minimum mean-square error STSA estimator, based on modeling speech and noise spectral components as statistically independent Gaussian random variables, which results in a significant reduction of the noise, and provides enhanced speech with colorless residual noise.
Journal ArticleDOI
A signal subspace approach for speech enhancement
Yariv Ephraim,H.L. Van Trees +1 more
TL;DR: The popular spectral subtraction speech enhancement approach is shown to be a signal subspace approach which is optimal in an asymptotic (large sample) linear minimum mean square error sense, assuming the signal and noise are stationary.
Journal ArticleDOI
Speech enhancement using a soft-decision noise suppression filter
R. McAulay,M. Malpass +1 more
TL;DR: In this paper, a spectral decomposition of a frame of noisy speech is used to attenuate a particular spectral line depending on how much the measured speech plus noise power exceeds an estimate of the background noise.
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